Astronomy and Astrophysics – Astronomy
Scientific paper
Sep 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aspc..411..247k&link_type=abstract
Astronomical Data Analysis Software and Systems XVIII ASP Conference Series, Vol. 411, proceedings of the conference held 2-5 No
Astronomy and Astrophysics
Astronomy
Scientific paper
We present a de-trending algorithm for the removal of trends in time series. Trends in time series could be caused by various systematic and random noise sources such as cloud passages, changes of airmass, telescope vibration or CCD noise. We determine the trends from subsets of stars that are highly correlated among themselves. These subsets are selected based on a hierarchical tree clustering algorithm. A bottom-up merging algorithm based on the departure from normal distribution in the correlation is developed to identify subsets, which we call clusters. After identification of clusters, we determine a trend per cluster by weighted sum of normalized light curves. We then use quadratic programming to de-trend all individual light curves based on these determined trends. Experimental results with synthetic light curves containing artificial trends and events are presented.
Alcock Charles
Bianco Federica B.
Byun Youngshin
Kim Dae Wook
Protopapas Pavlos
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